Rules for Biologically Inspired Adaptive Network Design

By A. Tero, S. Takagi, T. Saigusa, K. Ito, D. Bebber, M. Fricker, Kenji Yumiki, R. Kobayashi, T. Nakagaki. Science, 2010

904 citations recorded by the source corpus.

Miniature Transport Engineers In its vegetative phase, the slime mold Physarum polycephalum “slimes” its way through the world seeking food. As it explores, it links previously found food sources with tubular structures. Tero et al. (p. 439) report that if food sources are deposited on a plate in a pattern corresponding in miniature to the positions of the cities that surround Tokyo, the resulting network of Physarum tubules that develops is rather similar in structure to the railroad network that connects the Japanese cities. A model was produced that describes the adaptive network development displayed by the slime mold. This biologically inspired model might provide insight into how to implement properties like resistance of transport systems to local failures into similar human-designed systems. Human municipal transportation engineers might learn design strategies from the lowly slime mold. Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks—in this case, the Tokyo rail system. The core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical model that may be useful to guide network construction in other domains.

Subfields: Biomedical Engineering, Ecology, Evolution, Behavior and Systematics, Plant Science

View Paper: https://www.semanticscholar.org/paper/3881fa370a0a434d98936455e999e328cf297ef3

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Citations in the corpus

Untapped potential: exploiting fungi in bioremediation of hazardous chemicals (2011, background): “The organization of fungal networks has parallels with that of other foraging biological systems (for example, plant roots) and man-made infrastructures such as public suburban commuter railway system”
Meso-scale turbulence in living fluids (2012, background): “S imple forms of life, like amoebae or bacteria, self-organize into remarkable macroscopic patterns [1, 2], ranging from extended networks [3, 4] to complex vortices [5, 6, 7, 8, 9, 10] and swarms [11].”
Spatial Networks (2010, methodology): “The benefit/cost ratio could then be estimated by the quantity FT/` T which is a quantitative characterization of the trade-off between cost and efficiency [298].”
Control Principles of Complex Networks (2015, background): “Honed by evolution, these biological networks are examples of adaptive transportation networks, balancing real-world compromises between search strategy and transport efficiency (Tero et al., 2010).”
Biologicalisation: Biological transformation in manufacturing (2018, background): “Transport networks, for example, despite their importance have emerged without clear global design principles and were constrained by the priorities at their initiation [Tero et al., 2010].”